How to Use the Hive (Project Management) MCP in CrewAI

Deploy a team of autonomous CrewAI agents to manage your Hive projects. One researches, another tracks progress, and a third updates tasks.

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Connect Hive (Project Management) MCP to CrewAI

Create your Vinkius account to connect Hive (Project Management) to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Hive (Project Management) with CrewAI

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Perplexity

Multi-agent project management

The `get_action` tool gives your specialized agents direct access to specific task details. You assign a researcher agent to read the requirements while a separate execution agent writes the code. When the work finishes, a reporting agent calls `list_actions` to compile a summary of everything completed that day. They share memory, so the reporter knows exactly what the executor did.

Hierarchical task delegation

The `list_projects` tool lets your manager agent review the current portfolio layout. It analyzes the workload and decides which subordinate agent should handle the next phase. The manager then commands a subordinate to run `create_action` for each missing dependency. You get a self-organizing system that spots gaps in your roadmap and fills them automatically.

CrewAI MCP Server integration

The `list_labels` tool and its siblings plug straight into your crew configuration via this MCP Server. You pass the URL directly into the agent setup, and it immediately understands how to interact with your workspace. If you need strict boundaries, use the tool filter option. This restricts a junior agent to only reading data while the senior agent retains full write access.

Setup guide

Set up Hive (Project Management) MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Hive (Project Management) tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Hive (Project Management) Analyst",
    goal="Access and analyze Hive (Project Management) data via MCP.",
    backstory="Expert analyst with direct Hive (Project Management) access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Hive (Project Management) transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Hive (Project Management) Analyst",
        goal="Access and analyze Hive (Project Management) data via MCP.",
        backstory="Expert analyst with direct Hive (Project Management) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Hive (Project Management) transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Hive. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Hive (Project Management) MCP in CrewAI

Add the server URL to the array in your agent definition. For more granular control, import the HTTP server class and specify exactly which tools the agent can see.

Yes. You provide the MCP configuration to each agent that needs it. They will execute tools like `list_templates` independently while sharing the results in their collective memory.

Filter the tools at the agent level. Give your monitor agents access to read-only endpoints like `list_workspaces`, and reserve the creation tools for a single moderator agent.

The framework supports standard input, server-sent events, and streaming HTTP. Vinkius defaults to HTTP for remote connections, which fits perfectly with the crew setup.

Your agents process raw task descriptions and workspace hierarchies. The V8 Isolate Sandbox guarantees these operations happen in a completely ephemeral environment. Nothing is stored on disk.

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